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heimdall: Drift Adaptable Models

In streaming data analysis, it is crucial to detect significant shifts in the data distribution or the accuracy of predictive models over time, a phenomenon known as **concept drift**. The **heimdall** package aims to identify when concept drift occurs and provide methodologies for adapting models in non-stationary environments. It offers a range of state-of-the-art techniques for detecting concept drift and maintaining model performance. Additionally, **heimdall** provides tools for adapting models in response to these changes, ensuring continuous and accurate predictions in dynamic contexts. Methods for concept drift detection are described in Tavares (2022) <doi:10.1007/s12530-021-09415-z>.

Version: 1.0.737
Imports: stats, caret, daltoolbox, ggplot2, reticulate, pROC, car
Published: 2025-04-28
DOI: 10.32614/CRAN.package.heimdall
Author: Lucas Tavares [aut], Leonardo Carvalho [aut], Diego Carvalho [aut], Esther Pacitti [aut], Fabio Porto [aut], Eduardo Ogasawara ORCID iD [aut, ths, cre], Federal Center for Technological Education of Rio de Janeiro (CEFET/RJ) [cph]
Maintainer: Eduardo Ogasawara <eogasawara at ieee.org>
License: MIT + file LICENSE
URL: https://cefet-rj-dal.github.io/heimdall/, https://github.com/cefet-rj-dal/heimdall
NeedsCompilation: no
Materials: README
CRAN checks: heimdall results

Documentation:

Reference manual: heimdall.pdf

Downloads:

Package source: heimdall_1.0.737.tar.gz
Windows binaries: r-devel: heimdall_1.0.737.zip, r-release: heimdall_1.0.737.zip, r-oldrel: heimdall_1.0.717.zip
macOS binaries: r-release (arm64): heimdall_1.0.737.tgz, r-oldrel (arm64): heimdall_1.0.737.tgz, r-release (x86_64): heimdall_1.0.737.tgz, r-oldrel (x86_64): heimdall_1.0.737.tgz
Old sources: heimdall archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.